In the last 30 years or so, the acquisition of three-dimensional (3D) point clouds has become an important surveying technique for gathering geospatial information in indoor and outdoor environments. A 3D point cloud may include X, Y, and Z coordinates of a set of points in a 3D coordinate system. These points are often intended to represent the external surface of an object. 3D point clouds can be acquired by 3D scanners, stereo vision cameras, time-of-flight lidar systems, and the like.
Thanks to recent improvements in quality and productivity, 3D data are becoming mainstream in many applications, such as urban analysis, building monitoring, industrial modeling, digital terrain generation, forest monitoring, documentation of cultural heritage, among others. In spite of the great progress in the acquisition of 3D point clouds, there are still some outstanding issues in data processing and visualization of 3D point clouds. In particular, rendering of 3D scene remains a challenge, which often requires some expert users to be involved.